blackIn this section, we introduce various priors, which are roughly categorized as classical priors, and learning-based priors. The classical priors have canny, gradients, RTV, HOG, and LR-RGB, while latter one will consider the wireframes, L-Edges, and semantic segmentation. Learning-based priors employs the deep models to extract priors from images.
These priors will be negatively affected by masked images [1]}, as no visual content is available. Visualizations of these priors are in Fig. REF .
In this subsection, we still use the Place2 subset of 25,000 training and 500 validation images over 5 scenes for the pilot study.
